Is Extreme Learning Machine Effective for Multisource Friction Modeling? - Artificial Intelligence Applications and Innovations (AIAI 2015) Access content directly
Conference Papers Year : 2015

Is Extreme Learning Machine Effective for Multisource Friction Modeling?

Jacek Kabziński
  • Function : Author
  • PersonId : 991079

Abstract

The aim of this contribution is to discuss suitability of extreme learning machine (ELM) approach for modeling multisource friction for motion control purposes. The specific features of multisource friction in mechatronic systems are defined, the main aspects of friction modeling by a standard ELM are investigated and some modifications are proposed to make it more suitable for specific demands of the discussed task. This allows to formulate some general remarks concerning properties of ELM for function approximation.
Fichier principal
Vignette du fichier
978-3-319-23868-5_23_Chapter.pdf (380.35 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01385367 , version 1 (21-10-2016)

Licence

Attribution

Identifiers

Cite

Jacek Kabziński. Is Extreme Learning Machine Effective for Multisource Friction Modeling?. 11th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI 2015), Sep 2015, Bayonne, France. pp.318-333, ⟨10.1007/978-3-319-23868-5_23⟩. ⟨hal-01385367⟩
39 View
118 Download

Altmetric

Share

Gmail Facebook X LinkedIn More